With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Major Changes Since The First Edition
Creation of a now mature R package, rms, that replaces and greatly extends the Design library used in the first edition
Conversion of all of the book's code to R
Conversion of the book source into knitr reproducible document
All code from the text is executable and is on the web site
Use of color graphics and use of the ggplot2 graphics package
Scanned images were re-drawn
New text about problems with dichotomization of continuous variables and with classification (as opposed to prediction)
Expanded material on multiple imputation and predictive mean matching and emphasis on multiple imputation (using the Hmisc aregImpute function) instead of single imputation
Addition of redundancy analysis
Added a new section in Chapter 5 on bootstrap confidence intervals for rankings of predictors
Replacement of the U.S. presidential election data with analyses of a new diabetes dataset from NHANES using ordinal and quantile regression
More emphasis on semiparametric ordinal regression models for continuous Y, as direct competitors of ordinary multiple regression, with a detailed case study
A new chapter on generalized least squares for analysis of serial response data
The case study in imputation and data reduction was completely reworked and now focuses only on data reduction, with the addition of sparse principal components
More information about indexes of predictive accuracy
Augmentation of the chapter on maximum likelihood to include more flexible ways of testing contrasts as well as new methods for obtaining simultaneous confidence intervals
Binary logistic regression case study 1 was completely re-worked, now providing examples of model selection and model approximation accuracy
Single imputation was dropped from binary logistic case study 2
The case study in transform-both-sides regression modeling has been reworked using simulated data where true transformations are known, and a new example of the smearing estimator was added
Addition of 225 references, most of them published 2001-2014
New guidance on minimum sample sizes needed by some of the models
De-emphasis of bootstrap bumping for obtaining simultaneous confidence regions, in favor of a general multiplicity approach